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Record W4410294211 · doi:10.1136/bmjopen-2025-099673

Application of distributional cost-effectiveness analysis methodology in real-world studies: a scoping review protocol

2025· review· en· W4410294211 on OpenAlexaff
Troy Francis, Bethlehem Teshome, Aleksandra Stanimirovic, Valeria E. Rac

Bibliographic record

VenueBMJ Open · 2025
Typereview
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsGrey literaturePsychological interventionScopusHealth careMEDLINEProtocol (science)MedicineSystematic reviewEquity (law)Data scienceComputer scienceAlternative medicineNursing

Abstract

fetched live from OpenAlex

INTRODUCTION: Healthcare systems face the challenge of managing limited resources while addressing the growing demand for care and the need for equitable access. Traditional cost-effectiveness analyses focus on maximising health benefits but often fail to account for how these benefits are distributed across various populations, potentially increasing health inequities. As a result, there is increasing interest in distributional cost-effectiveness analysis (DCEA), which incorporates equity considerations by explicitly assessing how health outcomes and costs are shared among diverse populations. This scoping review explores the practical application of DCEA methodology in evaluating programs and interventions. We seek to learn more about the barriers to DCEA's application, highlighting its practical challenges, limited use globally and the steps necessary to integrate equity more effectively into implementing and adopting programs and interventions into healthcare policy and resource allocation. METHODS AND ANALYSIS: To evaluate the use of DCEA in the literature, a scoping review will follow Preferred Reporting Items for Systematic Reviews and Meta-Analyses-Scoping Review Extension guidelines. Systematic searches will be performed across scientific databases (MEDLINE, SCOPUS, BASE, APA Psych and JSTOR), grey literature sources (Google Custom Search Engine), and handsearching to identify eligible articles published from January 2015 to March 2025. No limits will be placed on language. Reviewers will independently chart data from eligible studies using standardised data abstraction. The collected information will be synthesised both quantitatively and narratively. ETHICS AND DISSEMINATION: Formal ethical approval is not necessary as this study will not collect primary data. The findings will be shared with professional networks, published in conference proceedings and submitted for peer-reviewed publication.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.249
metaresearch head score (Gemma)0.254
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.751
Threshold uncertainty score0.926

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2490.254
Meta-epidemiology (narrow)0.0060.007
Meta-epidemiology (broad)0.0130.015
Bibliometrics0.0220.020
Science and technology studies0.0050.008
Scholarly communication0.0100.010
Open science0.0070.007
Research integrity0.0130.010
Insufficient payload (model declined to judge)0.0710.022

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.881
GPT teacher head0.724
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designSystematic review
DomainMethods
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2025
Admission routes1
Has abstractyes

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